Alfnoor: A Retrieval Simulation of the Ariel Target List

In this work, we present Alfnoor, a dedicated tool optimised for population studies of exoplanet atmospheres. Alfnoor combines the latest version of the retrieval algorithm TauREx 3, with the instrument noise simulator ArielRad and enables the simultaneous retrieval analysis of a large sample of exo-atmospheres. We applied this tool to the Ariel list of planetary candidates and focus on hydrogen dominated, cloudy atmospheres observed in transit with the Tier-2 mode (medium Ariel resolution). As a first experiment, we randomised the abundances - ranging from 10$^{-7}$ to 10$^{-2}$ - of the trace gases, which include H$_2$O, CH$_4$, CO, CO$_2$ and NH$_3$. This exercise allowed to estimate the detection limits for Ariel Tier-2 and Tier-3 modes when clouds are present. In a second experiment, we imposed an arbitrary trend between a chemical species and the effective temperature of the planet. A last experiment was run requiring molecular abundances being dictated by equilibrium chemistry at a certain temperature. Our results demonstrate the ability of Ariel Tier-2 and Tier-3 surveys to reveal trends between the chemistry and associated planetary parameters. Future work will focus on eclipse data, on atmospheres heavier than hydrogen and will be applied also to other observatories.
Comment: 33 pages, 24 figures, Accepted in AJ